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AI Development • Integration • Automation

The Houston AI Development Company Built for Production

Cortex Texas AI is a Houston-based AI development company that designs, develops and integrates AI systems, automation platforms and custom software for businesses across Texas and the US.

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AI Strategy • Engineering • Integration • Automation

X120 Y290 X514 Y360 X300 Y522 CORTEX AI CORE AI Agents Voice AI Business Data CRM Knowledge Automation APIs

WHAT CORTEX DOES

AI Built for Real Business Operations

We combine artificial intelligence, software engineering and systems integration to build technology that works inside the way organizations actually operate.

01

DEVELOP

Purpose-built AI applications and intelligent products.

02

INTEGRATE

Connect AI with software, APIs, data and existing business systems.

03

AUTOMATE

Orchestrate workflows, communication and repetitive operations.

04

ENGINEER

Build the secure software foundation required for dependable AI systems.

CORE CAPABILITIES

Engineering Intelligence Into Your Business

From strategy through deployment, Cortex Texas AI builds the systems, integrations and automation required to turn AI into practical business capability.

01

AI Agents & Agentic Systems

AI agents that take multi-step action, calling your tools and systems to complete tasks rather than just answering questions.

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02

Custom AI Development

Purpose-built AI applications and models designed around your specific data, workflows and business logic, not a generic off-the-shelf tool.

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03

AI Integration & API Engineering

Connecting AI systems to your existing software stack, including CRMs, ERPs and legacy platforms, through secure, well-engineered API integration.

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04

Intelligent Process Automation

Combining AI judgment with reliable rules-based automation to eliminate repetitive manual work across your business processes.

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05

AI Voice & Conversational AI

Natural-sounding AI voice and chat agents that handle calls and conversations end-to-end, integrated with your real business systems.

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06

RAG & Enterprise Knowledge Systems

Retrieval-augmented AI systems that answer questions grounded in your own documents, with accurate, source-linked responses.

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From AI Capability to Business Outcome

Problem

Slow Customer Response

Outcome

24/7 Intelligent Customer Engagement

Problem

Repetitive Manual Work

Outcome

Automated Operational Workflows

Problem

Disconnected Systems

Outcome

Connected AI-Powered Operations

Problem

Knowledge Trapped in Documents

Outcome

Searchable Enterprise Intelligence

Problem

High-Volume Calls

Outcome

AI Voice Automation

Problem

Complex Internal Tasks

Outcome

AI Agents & Copilots

AI SOLUTIONS

Intelligence Designed Around Your Operations

01

Customer Service Automation

AI-driven chat, email and voice support that resolves routine customer questions instantly and escalates the rest to your team.

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02

Sales & Lead Automation

AI-powered lead response, qualification and follow-up that contacts new leads within minutes and keeps your CRM up to date automatically.

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03

AI Voice Receptionists

An AI-powered phone system that answers, routes and resolves calls around the clock, integrated directly with your scheduling and business systems.

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04

Internal AI Copilots

AI assistants that give your team instant, natural-language answers from internal documentation, tickets and institutional knowledge.

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05

Document Intelligence

AI-powered extraction that turns incoming PDFs, forms and scanned documents into structured, usable data automatically.

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06

Workflow & Back-Office Automation

AI and rules-based automation that eliminates repetitive back-office tasks like data entry, status updates and cross-system syncing.

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How Cortex Builds AI Systems

  1. 01

    DISCOVER

    Understand workflows, systems, bottlenecks and objectives.

  2. 02

    ARCHITECT

    Design the AI, data, software, integration and security architecture.

  3. 03

    BUILD

    Engineer and validate the solution.

  4. 04

    INTEGRATE

    Connect it with the organization's existing technology ecosystem.

  5. 05

    OPTIMIZE

    Measure, refine and expand as operational requirements evolve.

AI Built Around Industry Workflows

Domain-aware AI and automation built around how each industry actually operates.

Healthcare & Medical Services

AI-driven patient intake, scheduling and documentation support for clinics, practices and healthcare providers.

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DME & Home Healthcare

Automation for durable medical equipment providers and home healthcare agencies managing orders, referrals and recurring patient touchpoints.

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Logistics & Transportation

AI automation for dispatch communication, shipment status updates and back-office coordination in logistics and transportation operations.

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Professional Services

AI knowledge assistants and workflow automation for law firms, accounting practices, consultancies and other professional service firms.

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Real Estate

AI lead response, scheduling and document automation for real estate brokerages, property managers and agents.

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Retail & E-Commerce

AI customer support, order-status automation and product-knowledge assistants for retail and e-commerce businesses.

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The Technology Behind Intelligent Systems

Intelligence

OpenAI

Anthropic Claude

Gemini

Llama

Orchestration

LangChain

LangGraph

Knowledge

Qdrant

Pinecone

Weaviate

pgvector

Voice

Twilio

Speech-to-Text & Text-to-Speech

Engineering

Python

PHP / Laravel

Node.js

React

React Native

Data

PostgreSQL

MySQL

AI SYSTEM Identity Encryption Data Access Monitoring Audit

SECURITY & RESPONSIBLE AI

Secure AI by Design

We design the systems we build with the same data-handling discipline we would expect for our own business: access limited to what a workflow actually needs, integrations built against official APIs, and clear human oversight where decisions matter most.

Security Architecture

A layered approach to identity, access, data protection, encryption, monitoring and auditability helps ensure AI systems are engineered with security considered throughout the solution architecture.

  • Data Protection

    We design integrations to access only the data an AI workflow genuinely needs, and avoid retaining information longer than that workflow requires.

  • Controlled Access

    Administrative and integration access is scoped and credentialed per system, consistent with the sensitivity of the data involved.

  • Secure Integrations

    Connections to a client's CRM, scheduling and internal systems are built against each platform's official, authenticated APIs rather than ad-hoc workarounds.

  • Auditability

    Administrative actions and key automation events are logged, so activity inside a system we build can be reviewed after the fact.

  • Privacy-Conscious Architecture

    We favor architectures that touch and expose only the data required for a given AI task, rather than granting broad, unscoped access by default.

  • Responsible AI Implementation

    For higher-stakes or customer-facing decisions, we design review checkpoints and escalation paths rather than fully autonomous, unreviewed automation.

Thinking Beyond the Model

Practical perspectives on AI engineering, automation, integration and enterprise implementation.

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Implementation Guides·Oct 8, 2026

AI Call Routing, Intake and Scheduling for Medical and Professional Practices in Texas

How AI call routing, intake and appointment scheduling help medical, legal and accounting practices answer every call, capture the right details and book appointments, while staff keep control.

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AI Fundamentals·Sep 22, 2026

AI Agents vs. Traditional Automation: What Businesses Need to Know

Traditional automation follows fixed rules; AI agents reason about a goal and decide what to do. Here's how the two actually differ, and when each one is the right fit for a business process.

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Implementation Guides·Sep 15, 2026

How Long Does Custom AI Development Take?

Timelines vary with scope, but a focused custom AI application commonly takes a few weeks from requirements to a working production version, while larger multi-system projects take longer.

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AI Fundamentals·Sep 1, 2026

Vector Databases Explained

A vector database stores numeric representations of content and finds the closest matches by meaning, not exact keywords, making it the retrieval backbone behind most RAG and enterprise knowledge systems.

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Questions Business Leaders Ask About AI

Straightforward answers to the questions we hear most often from leadership teams evaluating AI.

AI integration is the process of connecting artificial intelligence capabilities, such as language models or automation logic, to a business's existing software systems (CRMs, scheduling tools, ERPs, websites) so the AI can access real data and take real actions. It is what turns an AI demo into something that actually works in production.

AI automation improves operations by handling repetitive, high-volume tasks, such as answering routine questions, extracting data from documents, or following up with leads, faster and more consistently than manual processes, freeing staff to focus on higher-value work. The impact depends on correctly identifying which specific processes benefit most, which is why Cortex Texas AI starts most engagements with an assessment rather than a fixed solution.

AI agents are AI systems that can plan multi-step tasks and take real action by calling external tools and APIs, rather than only answering questions in a conversation. Unlike a basic chatbot, an agent can, for example, look up an order, check availability, and complete a booking on a caller's behalf.

An AI voice receptionist answers incoming calls using speech recognition to understand the caller, a language model to interpret intent and generate a response, and speech synthesis to reply naturally, while connecting to systems like a calendar or CRM to actually complete tasks such as booking an appointment. Calls that fall outside its scope are transferred to a human with full context.

RAG (retrieval-augmented generation) is a technique that retrieves relevant passages from a company's own documents at the moment a question is asked, and provides those passages to an AI language model so its answer is grounded in real source material instead of relying only on general training knowledge. This significantly reduces incorrect or fabricated answers on company-specific questions.

Enterprise knowledge systems use AI (typically via RAG) to let employees or customers ask natural-language questions against large bodies of internal documentation, wikis or manuals and get accurate, sourced answers instantly, instead of manually searching through folders or asking a colleague. This is especially valuable for organizations where institutional knowledge is large, scattered or changes frequently.

Timelines vary by scope, but a focused custom AI application (a single agent, integration or knowledge assistant) commonly takes a few weeks from requirements to a working production version, while larger multi-system projects take longer. Cortex Texas AI scopes a realistic timeline during the strategy/discovery phase rather than quoting a generic estimate up front.

Cost depends on the scope and complexity of the project and on the seniority of the engineers it needs. Development is billed at $60 to $100 per hour: routine integration and automation work sits toward the lower end, while complex AI architecture and senior engineering sit toward the upper end. Every engagement starts with a discovery conversation, and you receive a scoped estimate before development begins, so the expected cost is clear up front.

Cortex Texas AI integrates with most systems that expose a REST API, webhook or documented data interface, including common CRMs, scheduling platforms, ERPs and industry-specific software, and builds custom middleware for older systems that lack a modern API. The specific integration approach is scoped per system during the project's discovery phase.

No. Cortex Texas AI's approach is to automate repetitive, well-defined tasks so staff can focus on the judgment-heavy and relationship-driven work AI is not suited for, and to keep a human in the loop for decisions that need one. Most engagements are framed around capacity and response-time improvements, not headcount reduction.

Sensitive data is protected through scoped access controls (AI systems only access the specific data a task requires), encryption in transit and at rest, audit logging of data access and automated actions, and human review checkpoints for high-impact or sensitive decisions. Specific data-handling requirements are discussed and designed for on a per-project basis rather than assumed.

Ready to Put AI to Work?

Tell us where your business is losing time, struggling with disconnected systems or relying on repetitive manual processes. We'll explore how AI and automation can be engineered around the way your organization actually operates.

Book an AI Strategy Call Contact Cortex Texas AI